Ensemble Forecasting at NMC: The Generation of Perturbations

Ensemble Forecasting at NMC: The Generation of Perturbations On 7 December 1992, The National Meteorological Center (NMC) started operational ensemble forecasting. The ensemble forecast configuration implemented provides 14 independent forecasts every day verifying on days 110. In this paper we briefly review existing methods for creating perturbations for ensemble forecasting. We point out that a regular analysis cycle is a breeding ground for fast-growing modes. Based on this observation, we devise a simple and inexpensive method to generate growing modes of the atmosphere.The new method, breeding of growing modes, or BGM, consists of one additional, perturbed short-range forecast, introduced on top of the regular analysis in an analysis cycle. The difference between the control and perturbed six-hour (first guess) forecast is scaled back to the size of the initial perturbation and then reintroduced onto the new atmospheric analysis. Thus, the perturbation evolves along with the time-dependent analysis fields, ensuring that after a few days of cycling the perturbation field consists of a superposition of fast-growing modes corresponding to the contemporaneous atmosphere, akin to local Lyapunov vectors.The breeding cycle has been designed to model how the growing errors are bred and maintained in a conventional analysis cycle through the successive use of short-range forecasts. The bred modes should thus offer a good estimate of possible growing error fields in the analysis. Results from extensive experiments indicate that ensembles of just two BGM forecasts achieve better results than much larger random Monte Carlo or lagged average forecast (LAF) ensembles. Therefore, the operational ensemble configuration at NMC is based on the BGM method to generate efficient initial perturbations.The only two methods explicitly designed to generate perturbations that contain fast-growing modes corresponding to the evolving atmosphere are the BGM and the method of Lorenz, which is based on the singular modes of the linear tangent model. This method has been adopted operationally at The European Centre for Medium-Range Forecasts (ECMWF) for ensemble forecasting. Both the BGM and the ECMWF methods seem promising, but since it has not yet been possible to compare in detail their operational performance we limit ourselves to pointing out some of their similarities and differences. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

Ensemble Forecasting at NMC: The Generation of Perturbations

Loading next page...
 
/lp/ams/ensemble-forecasting-at-nmc-the-generation-of-perturbations-RRzBcFwSiR
Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
D.O.I.
10.1175/1520-0477(1993)074<2317:EFANTG>2.0.CO;2
Publisher site
See Article on Publisher Site

Abstract

On 7 December 1992, The National Meteorological Center (NMC) started operational ensemble forecasting. The ensemble forecast configuration implemented provides 14 independent forecasts every day verifying on days 110. In this paper we briefly review existing methods for creating perturbations for ensemble forecasting. We point out that a regular analysis cycle is a breeding ground for fast-growing modes. Based on this observation, we devise a simple and inexpensive method to generate growing modes of the atmosphere.The new method, breeding of growing modes, or BGM, consists of one additional, perturbed short-range forecast, introduced on top of the regular analysis in an analysis cycle. The difference between the control and perturbed six-hour (first guess) forecast is scaled back to the size of the initial perturbation and then reintroduced onto the new atmospheric analysis. Thus, the perturbation evolves along with the time-dependent analysis fields, ensuring that after a few days of cycling the perturbation field consists of a superposition of fast-growing modes corresponding to the contemporaneous atmosphere, akin to local Lyapunov vectors.The breeding cycle has been designed to model how the growing errors are bred and maintained in a conventional analysis cycle through the successive use of short-range forecasts. The bred modes should thus offer a good estimate of possible growing error fields in the analysis. Results from extensive experiments indicate that ensembles of just two BGM forecasts achieve better results than much larger random Monte Carlo or lagged average forecast (LAF) ensembles. Therefore, the operational ensemble configuration at NMC is based on the BGM method to generate efficient initial perturbations.The only two methods explicitly designed to generate perturbations that contain fast-growing modes corresponding to the evolving atmosphere are the BGM and the method of Lorenz, which is based on the singular modes of the linear tangent model. This method has been adopted operationally at The European Centre for Medium-Range Forecasts (ECMWF) for ensemble forecasting. Both the BGM and the ECMWF methods seem promising, but since it has not yet been possible to compare in detail their operational performance we limit ourselves to pointing out some of their similarities and differences.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Dec 1, 1993

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off